Using Census Microdata for demographic research

1. CENSUS European Doctoral School of Demography 2009 May 19 Using Census Microdata for demographic research Sabine Springer, Christophe Bergouignan CENSUS project (INED, ODE, IEDUB)

2. Using Census Microdata for demographic research • Census microdata samples databases. • Census microdata what for ? • IECM-IPUMS databases an easy way to get census microdata. • Comparisons across time and space • International comparisons with IECM-IPUMS databases (the portugese example). • Studying internal migrations with census microdata. • Pointing out interactions between factors of mobility and type of move, • The particular case of interactions between fertility and mobility.

3. Census microdata samples databases.

4. Census microdata what for ? • Still few users • Availability and ethical issues (indirect identification, « sensitive » variables,…), recent answers of data suppliers, • Lack of variables and some kinds of inaccuracy (indirect estimates, answers relialability,…), • Researchers representations (« photograph of present », overestimation of innacuracy of indexes,…..). • Census microdata samples / Census aggregate macrodata, less availability and more sampling errors but : • More cross-sectional options (complex indexes, statistical models including variance of indidividuals, micro-simulations), • Analysis involving household numbers or family ties (families or households new classification, measuring behaviour of individuals according to households characteristics, indirect estimates of demographic indexes,…). • Census microdata samples / Survey micro-data, less variables and less accuracy for life-courses disaggregation, but : • More statistical significance/representativity : • Leading to more cross-sectional options (age-detailed or cohort-detailed analysis useful for phenomena with high age or cohort concentration, e. g. students migrations), • Leading to more spatial disaggregation (geographical interactions, local specificities). • Mostly a lower non-response rate (1% to 10% for censuses, 0% to 55% for surveys ; e. g. around 20% for EHF 1999 / around 2% for french 1999 census).

5. CENSUS IECM-IPUMS databases an easy way to get census microdata • IECM-IPUMS project : • Availability of census microdata, • Comparability of census microdata. • IECM-IPUMS website : • Metadata, • Microdata to download.

6. Comparison across time and space • Classification variability among countries • Data processing to harmonize (family ties,…), • Data collection (students home and generally households « members » living outside the dwelling,…), • Enumeration forms (previous residence,…), • National statistical « custody » (french « PCS »,…), • Multidimensionnal meanings of variables (e. g. : educational attainment,….).

7. CENSUS General problems in cross country comparison or in comparison in time Differences in the underlying concepts – meaning or interpretation Differences in the operational definitions of these concepts – meaning and interpretation Differences in the measure of the concept – choice of question and its wording, differences in the proposed answer categories Differences in the definition of the universe

8. CENSUS Example: Multigenerational households in southern Europe The tool Advantages Possibilities Limits Pitfalls Shortcomings The Analysis Descriptive: • Frequency • Composition • Function Comparison: • Change over time • Differences between countries

9. CENSUS Multigenerational households in Europe Why census micro data? Why IECM data base? Are there alternatives? What are multigenerational households? How can we identify them? What do we want to know about them?

10. CENSUS Comparison of multigenerational households across time and spacePortugal (1981, 1991, 2001), France, Italy Identification of • Household • Members • Generation • The same for the three censuses? • The same for the three countries?

11. CENSUS Identification of household Household Types • Private household • Institutional household • Collective household • Homeless household Info can be found on the IECM website under : Meta data: http://www.iecm-project.org/index.php?module=metadata&c=prt&y=1981 Source:http://www.iecm-project.org/index.php?module=gc&tid=6&css=2 Variable: http://international.ipums.org/international-action/groups.do

12. Fernando Casimiro, F. Casimiro, 2009, INE, Portugal

13. CENSUS Definition of private household • Portugal (1981, 1991, 2001) • Family • Group of persons living at the same dwelling and that have kinship relations among them ("de jure" or "de facto"), regardless of occupying the whole or part of the housing unit. A person who lives alone in a separate housing unit or who occupies, as a logder, a separate room (or rooms) of a housing unit, but does not have kinship relations with the other occupants • http://www.iecm-project.org/index.php?module=metadata&c=prt France (1990) Dwelling unit no definition given http://www.iecm-project.org/index.php?module=metadata&c=fra&y=1990 Italy (2001) Family The term household refers to a group of people, bound by marriage, kinship, affinity, adoption, guardianship or by emotional ties, who are partners and live in the same Municipality (even if still not registered in the Population Register residing in that Municipality). A household may also be composed of one individual only.https://international.ipums.org/international/samples.shtml#it Spain (1991) Housekeeping Group of people who, residing in the same dwelling, share expenses derived from the use of the dwelling and/or alimentation. Single person and multiperson households are to be considered. http://www.iecm-project.org/index.php?module=metadata&c=esp

14. CENSUS Portugal 1981

15. CENSUS Integrated - Group quarter status

16. CENSUS Not integrated

17. CENSUS Comparison

18. CENSUS France 1990

19. CENSUS Identification of the members • De jure or de facto census concept • Resident status • Problematic groups: • Students • Working migrants • Living together apart • Visitor, migrants (emigrants, imigrants) • Homeless persons, persons without a fixed living quarter

20. CENSUS Identification of the generation • Relationship with household head • Who is head of household? • Every categories allows the identification of a generation ? => Otherwise : Age

21. CENSUS Conclusion + + possibility of comparison between countries that does not exist otherwise + integrated variables that allow the comparison between countries + explicit meta data information and census documentation + unharmonized data available

22. CENSUS Conclusion - • translation not always correct • integrated variables– false reliability • Problems with data quality • particular problems for specific samples

23. CENSUS Conclusion = • IPUMS data base can not be better than the census itself, but it can indicate problems! • There is no alternative for certain research subjects